Nothing
requireNamespace("dplyr")
# Read in the test data
beesFlagged <- BeeBDC::beesFlagged
# Run the function
flagTibble <- flagSummaryTable(data = beesFlagged,
column = "scientificName",
outPath = tempdir(),
fileName = "/filterTable.csv")
# Get the number of 100% fails and 0% fails
fails100 <- sum(flagTibble$percentFailed == 100)
fails0 <- sum(flagTibble$percentFailed == 0)
# Test class
testthat::test_that("flagSummaryTable expected class", {
testthat::expect_type(flagTibble, "list")
})
# Test specific class
testthat::test_that("flagSummaryTable expected class", {
testthat::expect_true(any(stringr::str_detect(attributes(flagTibble)$class,
"tbl_df")))
})
# Test 100% fails size
testthat::test_that("flagSummaryTable 100% failed size test", {
testthat::expect_equal(fails100, 63)
})
testthat::test_that("flagSummaryTable 0% failed size test", {
testthat::expect_equal(fails0, 15)
})
# Test number of filtering columns
testthat::test_that("flagSummaryTable test the number of flag columns in and out are equal, minus two. Excluding '.summary'", {
testthat::expect_equal(colnames(beesFlagged %>%
dplyr::select(tidyselect::starts_with(".")) %>%
dplyr::select(!tidyselect::any_of(".summary"))) %>%
length - 2,
colnames(flagTibble %>%
dplyr::select(tidyselect::starts_with(".")) %>%
dplyr::select(!tidyselect::any_of(".summary"))) %>%
length)
})
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